User stories are essential in agile software development for capturing software requirements, yet concerns over their quality persist globally. While prior studies have evaluated user story quality using practitioners and artificial intelligence, they primarily focus on general settings. This study addresses a gap by evaluating the quality of student-generated user stories in an educational context, specifically in Indonesia. The objective of this study is to compare evaluations by human evaluators and ChatGPT using the Quality User Story (QUS) Framework and evaluate the quality of the student-generated user story compared to the global studies. A total of 951 user stories from 103 student software projects were analyzed. Evaluations were conducted by three human evaluators and ChatGPT (GPT-4o). Percentage Agreement and Cohen’s Kappa measured inter-rater agreement, while the McNemar Test assessed statistical significance, and effect sizes were examined using Cohen’s g. Results show generally high agreement between human and ChatGPT evaluations, but lower consistency in several criteria, such as Conceptually Sound, Independent, and Unambiguous. Only four of the thirteen criteria—Conflict-Free, Unique, Well-Formed, and Atomic—showed no significant differences. Most criteria showed small to medium effect sizes, whereas Complete exhibited a large practical difference. Common quality issues among students included Uniform, Independent, and Complete (set criteria), Atomic, Conceptually Sound, and Unambiguous (individual criteria), with overlap observed in global studies. This study shows that ChatGPT can support user story evaluation in educational settings when guided by clear rubrics and validated by humans. It also offers practical insights for educators by identifying criteria that require stronger emphasis in teaching, particularly in software engineering education in Indonesia.

User stories (US) play a vital role in requirement engineering, yet they often encounter challenges such as ambiguity, inefficiency, and low quality. Many Indonesian universities face difficulties in equipping students with practical skills essential for crafting effective US, despite efforts to align curricula with industry standards. Moreover, existing approaches that integrate design thinking (DT) into educational settings are limited, as they either do not adequately emphasize the US or do not yet address the unique needs of educational contexts. This study presents an innovative US-DT integrated teaching model to enhance students’ experience developing industry-relevant user stories. Utilizing an action research methodology, the study incorporates surveys and literature reviews to guide the model's development. The model was tested with a sample of Indonesian software engineering undergraduate students, focusing on evaluating their satisfaction levels through metrics such as perceived usefulness (PU), learning motivation (LM), learning satisfaction (LS), and perceived ease of use (PEOU). The impact of the model was assessed via the Mann-Whitney U Test and Cliff’s Delta effect size, comparing it against regular teaching methods. Results demonstrate significant improvements in PU, LM, and LS, indicating effectiveness, although PEOU remains a key limitation requiring further refinement. Future research should focus on improving PEOU by refining teaching strategies, optimizing session management, introducing preparatory workshops, and extending the model’s application to different student groups to validate and broaden its educational impact. The findings suggest that adapting US and DT from industry can notably enrich student learning experiences.